Employing machine learning to enhance fracture recovery insights through gait analysis
Mostafa Rezapour,
Rachel B. Seymour,
Stephen H. Sims
et al.
Abstract:This study aimed to explore the potential of gait analysis coupled with supervised machine learning models as a predictive tool for assessing post‐injury complications such as infection, malunion, or hardware irritation among individuals with lower extremity fractures. We prospectively identified participants with lower extremity fractures at a tertiary academic center. These participants underwent gait analysis with a chest‐mounted inertial measurement unit device. Using customized software, the raw gait data… Show more
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